A fast and reliable method for the comparison of covariance matrices

Understand

Covariance matrices are important tools for obtaining reliable parameter constraints.

• Advancements in cosmological surveys lead to larger data vectors and, consequently, increasingly complex covariance matrices, whose number of elements grows as the square of the size of the data vector.
• The most straightforward way of comparing these matrices, in terms of their ability to produce parameter constraints, involves a full cosmological analysis, which can be very computationally expensive.
• Using the concept and construction of compression schemes, which have become increasingly popular, we propose a fast and reliable way of comparing covariance matrices.